Microservices maturity model - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding the Basic Level of Microservices Maturity

At the initial level of the microservices maturity model, what is the primary characteristic of the services?

A Services are tightly coupled and often deployed together as a monolith.

B Services are loosely coupled and independently deployable with automated testing.

C Services communicate asynchronously using event-driven architecture.

D Services have full observability with distributed tracing and monitoring.

💡 Hint

Think about the starting point before microservices are fully adopted.

The initial level often represents a monolithic or tightly coupled architecture where services are not independently deployable.

❓ Architecture

intermediate

Identifying Characteristics of a Mature Microservices Architecture

Which of the following best describes a mature microservices architecture in terms of service communication and deployment?

A Services communicate synchronously via REST APIs and are deployed together in a single container.

B Services are independently deployable, communicate asynchronously using messaging, and have automated CI/CD pipelines.

C Services share a common database and are deployed as a single unit.

D Services rely on manual deployment and use direct database calls for communication.

💡 Hint

Consider how mature microservices handle deployment and communication for scalability and resilience.

Mature microservices are independently deployable, use asynchronous communication to reduce coupling, and have automated deployment pipelines.

❓ scaling

advanced

Scaling Challenges in Microservices Maturity

At an advanced maturity level, what is a common challenge when scaling microservices, and how is it typically addressed?

A Scaling is limited by a shared database; it is addressed by sharding the database per service.

B Scaling is limited by lack of monitoring; it is addressed by removing logging to improve performance.

C Scaling is limited by manual deployments; it is addressed by reducing the number of services.

D Scaling is limited by synchronous calls; it is addressed by introducing asynchronous messaging and event-driven patterns.

💡 Hint

Think about communication patterns that affect scalability.

Synchronous calls create bottlenecks; asynchronous messaging helps services scale independently and improves resilience.

❓ tradeoff

advanced

Tradeoffs in Microservices Observability at High Maturity

What is a key tradeoff when implementing full observability (distributed tracing, logging, monitoring) in a highly mature microservices system?

A Full observability improves debugging but adds overhead and can impact system performance.

B Improved observability reduces system complexity but increases deployment time.

C Observability eliminates the need for automated testing, reducing development effort.

D Implementing observability removes the need for service-level agreements (SLAs).

💡 Hint

Consider the cost of collecting and processing detailed telemetry data.

While observability helps detect and diagnose issues, it introduces resource overhead that can affect performance.

❓ estimation

expert

Estimating Service Count for Microservices Maturity Transition

A company currently has a monolithic application with 100,000 lines of code. They plan to transition to microservices by splitting the monolith into services averaging 5,000 lines of code each. Approximately how many microservices will they have after the transition?

A 50 microservices

B 200 microservices

C 20 microservices

D 500 microservices

💡 Hint

Divide the total lines of code by the average size per service.

100,000 lines / 5,000 lines per service = 20 services.